Target Trial Emulation brings the logic of randomized trials into real-world data
Target Trial Emulation does not replace randomized controlled trials, but it applies their logic and rigor to real-world data analysis.
Analyzing electronic health record (EHR) data has already provided us with new insights in medical research and holds great promise for the future.
Unfortunately, many of the EHR systems were not designed with retrospective scientific study in mind and much of the interesting information lies in digital, but unstructured form. The largest source for this unstructured information in the hospital are different kinds of dictations and written notes that describe the patients’ status.
In the video, I quickly go over some of the approaches that we have taken at the Auria Biobank in analyzing such information and show some examples about the promising results we have obtained. Our tools vary from the trivial but very effective regular expressions all the way up to neural net driven vector space representations of words.
The author of this post is Antti Karlsson, PhD, Development Manager at Auria Biobank (picture by Mikko Tukiainen).
Target Trial Emulation does not replace randomized controlled trials, but it applies their logic and rigor to real-world data analysis.
The data team keeps Medaffcon's research projects on track and ensures that the research findings are scientifically sound. At the heart of the team’s work is the processing and analysis of patient data, particularly in Real-World Evidence (RWE) studies.
Medaffcon's European Lung Cancer Congress (ELCC) poster showcased key findings from a recent study on non-small cell lung cancer (NSCLC).